Search results for: deep eutectic solvent

Authors: Ahmed Boucherit, Hussein Khalaf, Eduardo Paredes, José Luis Todolí

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Solvent extraction studies of molybdenum (VI) with two organophosphorus reagents namely TBP and D2EHPA have been carried out from aqueous acidic solutions of HCl, H2SO4 and H3PO4 under microwave irradiations. The extraction efficiencies of the investigated extractants in the extraction of molybdenum (Vl) were compared. Extraction yield was found unchanged when microwave power varied in the range 20-100 Watts from H2SO4 or H3PO4 but it decreases in the range 20-60 Watts and increases in the range 60-100 Watts when TBP is used for extraction of molybdenum (VI) from 1 M HCl solutions. Extraction yield of molybdenum (VI) was found higher with TBP for HCl molarities greater than 1 M than with D2EHPA for H3PO4 molarities lower than 1 M. Extraction yield increases with HCl molarities in the range 0.50 - 1.80 M but it decreases with the increase in H2SO4 and H3PO4 molarities in the range of 0.05 - 1 M and 0.50 - 1 M, respectively.

Keywords: extraction, molybdenum, microwave, solvent

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Authors: Imen Abid, Rachel Calvet, Michel Baltas

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Flavonoids are secondary metabolites that belong to a polyphenolic class, present in fruits and vegetables, playing a significant role in biological systems. The structural variations of these flavonoids are associated with many biological and pharmacological activities (antioxidant, anti-inflammatory, anticancer, antibacterial, antifungal, antiviral, and antimalarial). Given their importance in plants and health-promoting roles in humans, significant efforts have been devoted towards their isolation of flavonoids and chemical elaboration (organic synthesis). But with the increasing public concern over environmental degradation and future resources, it is of great importance for chemists to come up with different approaches, less hazardous to human health and the environment. Being employed in large amounts, the solvents used in organic synthesis are high on the list of environmental pollutants. To overcome these problems, our approach is to develop unconventional processes involving solvent-free conditions. The application of mechanical forces to solvent-free or solvent-less reaction mixtures through the use of ball mills offers many advantages over traditional solvent-based strategies. It is one of the unconventional activation methods, which makes it possible to overcome the use of solvents, in the context of green chemistry and more respectful of the environment.

Keywords: organic synthesis, green chemistry, mecanochemistry, pharmaceutical molecules

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Authors: Hanan Alenezi

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Membrane performance depends on the kind of solvent used in preparation. A membrane made by Polyetherimide (PEI) was evaluated for gas separation using X-Ray Diffraction (XRD), Scanning electron microscope (SEM), and Energy Dispersive X-Ray Spectroscopy (EDS). The purity and the thickness are detected to evaluate the membrane in order to optimize PEI membrane preparation.

Keywords: Energy Dispersive X-Ray Spectroscopy (EDS), Membrane, Polyetherimide PEI, Scanning electron microscope (SEM), Solvent, X-Ray Diffraction (XRD)

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Authors: Sunny Arora, Meghal A. Desai

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An impetus towards green consumerism and implementation of sustainable techniques, consumption of natural products and utilization of environment friendly techniques have gained accelerated acceptance. Butein, a natural colorant, has many medicinal properties apart from its use in dyeing industries. Extraction of butein from the flowers of flame of forest was carried out using ultrasonication bath. Solid loading (2-6 g), extraction time (30-50 min), volume of solvent (30-50 mL) and types of solvent (methanol, ethanol and water) have been studied to maximize the yield of butein using the Taguchi method. The highest yield of butein 4.67% (w/w) was obtained using 4 g of plant material, 40 min of extraction time and 30 mL volume of methanol as a solvent. The present method provided a greater reduction in extraction time compared to the conventional method of extraction. Hence, the outcome of the present investigation could further be utilized to develop the method at a higher scale.

Keywords: butein, flowers of Flame of the Forest, Taguchi method, ultrasonic bath

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Authors: Romisaa Ali

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The Policy Gradient approach is one of the deep reinforcement learning families that combines deep neural networks (DNN) with reinforcement learning RL to discover the optimum of the control problem through experience gained from the interaction between the robot and its surroundings. In contrast to earlier policy gradient algorithms, which were unable to handle these two types of error because of over-or under-estimation introduced by the deep neural network model, this article will discuss the state-of-the-art SOTA policy gradient technique, trust region policy optimization (TRPO), by applying this method in various environments compared to another policy gradient method, the Proximal Policy Optimization (PPO), to explain their robust optimization, using this SOTA to gather experience data during various training phases after observing the impact of hyper-parameters on neural network performance.

Keywords: deep neural networks, deep reinforcement learning, proximal policy optimization, state-of-the-art, trust region policy optimization

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Authors: Paresh Patel, Priya Patel, Vaidehi Sorathiya, Navin Sheth

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The aim of present work was to fabricate Salmeterol Xinafoate (SX) metered dose inhaler (MDI) for asthma and to evaluate the SX loaded solid lipid nanoparticles (SLNs) for pulmonary delivery. Solid lipid nanoparticles can be used to deliver particles to the lungs via MDI. A modified solvent emulsification diffusion technique was used to prepare Salmeterol Xinafoate loaded solid lipid nanoparticles by using compritol 888 ATO as lipid, tween 80 as surfactant, D-mannitol as cryoprotecting agent and L-leucine was used to improve aerosolization behaviour. Box-Behnken design was applied with 17 runs. 3-D surface response plots and contour plots were drawn and optimized formulation was selected based on minimum particle size and maximum % EE. % yield, in vitro diffusion study, scanning electron microscopy, X-ray diffraction, DSC, FTIR also characterized. Particle size, zeta potential analyzed by Zetatrac particle size analyzer and aerodynamic properties was carried out by cascade impactor. Pre convulsion time was examined for control group, treatment group and compare with marketed group. MDI was evaluated for leakage test, flammability test, spray test and content per puff. By experimental design, particle size and % EE found to be in range between 119-337 nm and 62.04-76.77% by solvent emulsification diffusion technique. Morphologically, particles have spherical shape and uniform distribution. DSC & FTIR study showed that no interaction between drug and excipients. Zeta potential shows good stability of SLNs. % respirable fraction found to be 52.78% indicating reach to the deep part of lung such as alveoli. Animal study showed that fabricated MDI protect the lungs against histamine induced bronchospasm in guinea pigs. MDI showed sphericity of particle in spray pattern, 96.34% content per puff and non-flammable. SLNs prepared by Solvent emulsification diffusion technique provide desirable size for deposition into the alveoli. This delivery platform opens up a wide range of treatment application of pulmonary disease like asthma via solid lipid nanoparticles.

Keywords: salmeterol xinafoate, solid lipid nanoparticles, box-behnken design, solvent emulsification diffusion technique, pulmonary delivery

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Authors: Beata Pospiech

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Separation of metal ions from aqueous solutions is important as well as difficult process in hydrometallurgical technology. This process is necessary for obtaining of clean metals. Solvent extraction and membrane processes are well known as separation methods. Recently, ionic liquids (ILs) are very often applied and studied as extractants and carriers of metal ions from aqueous solutions due to their good extractability properties for various metals. This work discusses a method to separate copper(II) and iron(III) from hydrochloric acid solutions by solvent extraction and transport across polymer inclusion membranes (PIM) with the selected ionic liquids as extractants/ion carriers. Cyphos IL 101 (trihexyl(tetradecyl)phosphonium chloride), Cyphos IL 104 (trihexyl(tetradecyl)phosphonium bis(2,4,4 trimethylpentyl)phosphi-nate), trioctylmethylammonium thiosalicylate [A336][TS] and trihexyl(tetradecyl)phosphonium thiosalicylate [PR4][TS] were used for the investigations. Effect of different parameters such as hydrochloric acid concentration in aqueous phase on iron(III) and copper(II) extraction has been investigated. Cellulose triacetate membranes with the selected ionic liquids as carriers have been prepared and applied for transport of iron(IIII) and copper(II) from hydrochloric acid solutions.

Keywords: copper, iron, ionic liquids, solvent extraction

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Authors: Jayprakash Yadav, Nivedita Patra

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Polyhydroxybutyrate (PHB) is an interesting material in the field of medical science, pharmaceutical industries, and tissue engineering because of its properties such as biodegradability, biocompatibility, hydrophobicity, and elasticity. PHB is naturally accumulated by several microbes in their cytoplasm during the metabolic process as energy reserve material. PHB can be extracted from cell biomass using halogenated hydrocarbons, chemicals, and enzymes. In this study, a cheaper and non-toxic solvent, acetone, was used for the extraction process. The different parameters like acetone percentage, and solvent pH, process temperature, and incubation periods were optimized using the Response Surface Methodology (RSM). RSM was performed and the determination coefficient (R2) value was found to be 0.8833 from the quadratic regression model with no significant lack of fit. The designed RSM model results indicated that the fitness of the response variable was significant (P-value < 0.0006) and satisfactory to denote the relationship between the responses in terms of PHB recovery and purity with respect to the values of independent variables. Optimum conditions for the maximum PHB recovery and purity were found to be solvent pH 7, extraction temperature - 43 °C, incubation time - 70 minutes, and percentage acetone – 30 % from this study. The maximum predicted PHB recovery was found to be 0.845 g/g biomass dry cell weight and the purity was found to be 97.23 % using the optimized conditions.

Keywords: acetone, PHB, RSM, halogenated hydrocarbons, extraction, bacillus subtilis.

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Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart

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The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.

Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition

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Authors: Rui Tu, Yakui Bai, Huailin Li

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The lead-bismuth eutectic (LBE) alloy is a promising candidate of coolant in the fast neutron reactors and accelerator-driven systems (ADS) because of its good properties, such as low melting point, high neutron yields and high thermal conductivity. Although the corrosion of the structure materials caused by the liquid metal (LM) coolant is a challenge to the safe operating of a lead-bismuth eutectic nuclear reactor. Thermodynamic theories, experiential formulas and experimental data can be used for explaining the maintenance of the protective oxide layers on stainless steels under satisfaction oxygen concentration, but the atomic scale insights of such anti-corrosion mechanisms are little known. In the present work, the first-principles calculations are carried out to study the effects of oxygen partial pressure on the formation energies of the liquid metal coolant relevant impurity defects in the anti-corrosion oxide films on the surfaces of the structure materials. These approaches reveal the microscope mechanisms of the corrosion of the structure materials, especially for the influences from the oxygen partial pressure. The results are helpful for identifying a crucial oxygen concentration for corrosion control, which can ensure the systems to be operated safely under certain temperatures.

Keywords: oxygen partial pressure, liquid metal coolant, TDDFT, anti-corrosion layer, formation energy

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Authors: Lokes Parvatha Kumaran S., Sakthi Jay Mahenthar C., Sathyaprakash P., Jayakumar V., Shobanadevi A.

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With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network.

Keywords: quantum computing, quantum machine learning, variational quantum circuit, deep reinforcement learning, quantum information encoding scheme

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: dialogue management, response generation, deep learning, evaluation

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Authors: Atef Ahmad Bleibel

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Most codes of practice, like ACI 318-14, require the use of strut-and-tie modeling to analyze and design reinforced concrete deep beams. Though, investigations that conducted on deep beams do not include ring deep beams of influential parameters. This work presents an analytical parametric study using strut-and-tie modeling stated by ACI 318-14 to predict load capacity of 20 reinforced concrete ring deep beam specimens with different parameters. The parameters that were under consideration in the current work are ring diameter (Dc), number of supports (NS), width of ring beam (bw), concrete compressive strength (f'c) and width of bearing plate (Bp). It is found that the load capacity decreases by about 14-36% when ring diameter increases by about 25-75%. It is also found that load capacity increases by about 62-189% when number of supports increases by about 33-100%, while the load capacity increases by about 25-75% when the beam ring width increases by about 25-75%. Finally, it is found that load capacity increases by about 24-76% when compressive strength increases by about 24-76%, while the load capacity increases by about 5-16% when Bp increases by about 25-75%.

Keywords: load parameters, reinforced concrete, ring deep beam, strut and tie

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Authors: Jawad Alzeer

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Natural products are well recognized as sources of drugs in several human ailments. To investigate the impact of variable extraction techniques on the cytotoxic effects of medicinal plant extracts, 5 well-known medicinal plants from Palestine were extracted with 90% ethanol, 80% methanol, acetone, coconut water, apple vinegar, grape vinegar or 5% acetic acid. The resulting extracts were screened for cytotoxic activities against three different cancer cell lines (B16F10, MCF-7, and HeLa) using a standard resazurin-based cytotoxicity assay and Nile Blue A as the positive control. Highly variable toxicities and tissue sensitivity were observed, depending upon the solvent used for extraction. Acetone consistently gave lower extraction yields but higher cytotoxicity, whereas other solvent systems gave much higher extraction yields with lower cytotoxicity. Interestingly, coconut water was found to offer a potential alternative to classical organic solvents; it gave consistently highest extraction yields, and in the case of S. officinalis L., highly toxic extracts towards MCF-7 cells derived from human breast cancer. These results demonstrate how the cytotoxicity of plant extracts can be inversely proportional to the yield, and that solvent selection plays an important role in both factors.

Keywords: plant extract, natural products, anti cancer drug, cytotoxicity

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Authors: S. V. Patil , S. K. Sahoo, K. Y. Chougule, S. S. Patil

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Spherically agglomerated crystals of Pioglitazone hydrochloride (PGH) with improved flowability and compactibility were successfully prepared by emulsion solvent diffusion method. Plane agglomerates and agglomerates with additives: polyethylene glycol 6000 (PEG), polyvinyl pyrrolidone (PVP) and β cyclodextrin (β-CD) were prepared using methanol, chloroform and water as good solvent, bridging liquid and poor solvent respectively. Particle size, flowability, compactibility and packability of plane, PEG and β-CD agglomerates were preferably improved for direct tableting compared with raw crystals and PVP agglomerates of PGH. These improved properties of spherically agglomerated crystals were due to their large and spherical shape and enhanced fragmentation during compaction which was well supported by increased tensile strength and less elastic recovery of its compact. X-ray powder diffraction and differential scanning calorimetry study were indicated polymorphic transition of PGH from form II to I during recrystallization but not associated with chemical transition indicated by fourier transforms infrared spectra.

Keywords: spherical crystallization, pioglitazone hydrochloride, compactibility, packability

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Authors: Parya Nasehi, Mohammad Kazem Mohammadi

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3,4-dihydropyrimidin-2(1H)-thiones were synthesized in the presence of Ag nanoparticle/melamine sulfonic acid (MSA) supported on alumina. The reaction was carried out at 110 oC for 20 min under solvent free conditions. This method have some advantages such as good yield, mild reaction conditions, ease of operation and work up, short reaction time and high product purity.

Keywords: nanoparticle melamine sulfonic acid, Al2O3, Biginelli reaction, 3, 4-dihydropyrimidin-2(1H, solvent free

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Authors: Shilpa Bhilegaonkar, Ram Gaud

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Candesartan cilexetil is a poorly soluble antihypertensive agent with solubility limited bioavailability (15%). To initiate process of solubilisation, it is very much necessary to displace the air at the surface and wet the drug surface with a solvent, with which drug is compatible. Present research adopts the same principle to improve solubility and dissolution of candesartan cilexetil. Solvents used here are surfactant and modified surfactant in different drug: solvent (1:1-1:9) ratio’s for preparation of adsorbates. Adsorbates were then converted into free flowing powders as liquisolid compacts and compressed to form tablets. Liquisolid compacts were evaluated for improvement in saturation solubility and dissolution of candesartan cilexetil. All systems were evaluated for improvement in saturation solubility and dissolution in different medias such as water, 0.1 N HCl, Phosphate buffer pH 6.8 and media given by office of generic drugs along with other physicochemical testing. All systems exhibited a promising advantage in terms of solubility and dissolution without affecting the drug structure as confirmed by IR and XRD. No considerable advantage was seen of increasing solvent ratio with drug.

Keywords: candesartan cilexetil, improved dissolution, solubility, liquisolid

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Authors: M. Bouhoun Ali, A. Y. Badjah Hadj Ahmed, M. Attou, A. Elias, M. A. Didi

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In this paper, the solvent extraction of uranium(VI), plutonium(IV) and thorium(IV) from aqueous solutions using 1-hydroxyhexadecylidene-1,1-diphosphonic acid (HHDPA) in treated kerosene has been investigated. The HHDPA was previously synthesized and characterized by FT-IR, 1H NMR, 31P NMR spectroscopy and elemental analysis. The effects contact time, initial pH, initial metal concentration, aqueous/organic phase ratio, extractant concentration and temperature on the extraction process have been studied. An empirical modelling was performed by using a 25 full factorial design, and regression equation for extraction metals was determined from the data. The conventional log-log analysis of the extraction data reveals that ratios of extractant to extracted U(VI), Pu(IV) and Th(IV) are 1:1, 1:2 and 1:2, respectively. Thermodynamic parameters showed that the extraction process was exothermic heat and spontaneous. The obtained optimal parameters were applied to real effluents containing uranium(VI), plutonium(IV) and thorium(IV) ions.

Keywords: solvent extraction, uranium, plutonium, thorium, 1-hydroxyhexadecylidene-1-1-diphosphonic acid, aqueous solution

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Authors: Poonam Yadav, Dong Bok Lee

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Raman spectroscopy was used for characterization of multi-wall carbon nanotube (MWNT) and Polycarbonate/multi-wall carbon nanotube (PC/MWNT) based fibers with 0.55% and 0.75% of MWNT (PC/MWNT55 and PC/MWNT75). PC/MWNT55 and PC/MWNT75 fibers was prepared by melt spinning device using nanocomposites made by two different route, viz., solvent casting and melt extrusion. Fibers prepared from melt extruded nanocomposites showed smooth and uniform morphology as compared to solvent casting based nanocomposites. The Raman mapping confirmed that the melt extruded based nanocomposites had better dispersion of MWNT in Polycarbonate (PC) than solvent casting carbon nanotube.

Keywords: dispersion, melt extrusion, multi-wall carbon nanotube, mapping

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Delowar Hossain, Genci Capi

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This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: deep learning, genetic algorithm, object recognition, robot grasping

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Authors: M. Abdoul-Hakim, A. Zeroual, H. Garmes

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2-Chlorobenzimidazoles are amphoteric compounds and versatile intermediates for the construction of polycyclic heterocycles. In this theoretical study performed by DFT at the B3LYP/6-311+G(d,p) level, we showed that the most likely route to obtain benzimidazo[1,2-d]oxadiazole from the reaction of 2-Chlorobenzimidazole with benzonitrile N-oxide involves the presence of anionic species, a concerted mechanism is not possible. The inclusion of the effect of the polar protic solvent (MeOH) favors the course of the reaction. The key interactions causing bond formation and breakage were identified by ELF topological analysis.

Keywords: benzimidazo[1, 2-d]oxadiazole, benzonitrile N-oxide, DFT, ELF, polycyclic heterocycles

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Authors: Mohammad H. Al-Sayah, Khalid Jarrah, Soleiman Hisaindee

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Hydrophobic sorbents are usually used to remove oil spills from water surfaces. In this study, the hydrophilic fibers of natural cotton were chemically modified with a solvent-free process to modify them into hydrophobic fibers that can remove oil from water surfaces. The cellulose-based fibers of cotton were reacted with trichlorosilanes through gas-solid reaction in a dry chamber. Cotton fibers were exposed to vapors of four different chloroalkylsilanes at room temperature for 24 hours. The chlorosilanes were namely trichloromethylsilane, dichlorodimethyl silane, butyltrichlorosilane, and trichloro (3,3,3-trifluoropropyl) silane. The modified cotton fibers were characterized by IR-spectroscopy, thermogravimetric analysis (TGA) and Scanning Electron Microscopy/Energy Dispersive X-Ray Spectroscopy (SEM-EDS). The degree of substitution for each of the grafted alkyl groups was in the range between 0.1 and 0.3 per glucose residue. As a result of sialylation, the cotton fibers became hydrophobic; this was reflected by water contact-angle measurements of the fibers which increased from zero for the unmodified cotton to above 100 degrees for the modified fibers. In addition, the adsorption capacity of the fibers for oil from water surfaces increased by about five times that of the unmodified cotton reaching 18 g oil/g of cotton modified by dimethyl substituted silyl ethers. The optimal fiber-oil contact time and temperature for adsorption were 10 mins at 25°C, respectively. Therefore, the efficacy of cotton fibers to remove oil spills from contaminated water surfaces was significantly enhanced by using a simple solvent-free and environment-friendly process.

Keywords: gas-solid silyl reaction, modified cellulose, solvent-free, oil pollution, cotton

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Authors: Hamida Y. Mostafa, Ghada E. Khedr, Dina M. Abd El-Aty

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Sulfur compound removal from petroleum fractions is a critical component of environmental protection demands. Solvent extraction, oxidative desulfurization, or hydro-treatment techniques have traditionally been used as the removal processes. While all methods were capable of eliminating sulfur compounds at moderate rates, they had some limitations. A major problem with these routes is their high running expenses, which are caused by their prolonged operation times and high energy consumption. Therefore, new methods for removing sulfur are still necessary. In the current study, a simple assisted desulfurization system for gas oil fraction has been successfully developed using acetonitrile and methanol as a solvent under microwave irradiation. The key variables affecting sulfur removal have been studied, including microwave power, irradiation time, and solvent to gas oil volume ratio. At the conclusion of the research that is being presented, promising results have been found. The results show that a microwave-assisted extractive desulfurization method had remove sulfur with a high degree of efficiency under the suitable conditions.

Keywords: extractive desulfurization, microwave assisted extraction, petroleum fractions, acetonitrile and methanol

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Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

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Authors: M. Dehghan, R. Al-Mahaidi, I. Sbarski

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An industrial epoxy adhesive used in Carbon Fiber Reinforced Polymer (CFRP)-strengthening systems was modified by dispersing multi-walled carbon nanotubes (MWCNTs). Nanocomposites were fabricated using solvent-assisted dispersion method and ultrasonic mixing. Thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA) and tensile tests were conducted to study the effect of nanotubes dispersion on the thermal and mechanical properties of the epoxy composite. Experimental results showed a substantial enhancement in the decomposition temperature and tensile properties of epoxy composite, while, the glass transition temperature (Tg) was slightly reduced due to the solvent effect. The morphology of the epoxy nanocomposites was investigated by SEM. It was proved that using solvent improves the nanotubes dispersion. However, at contents higher than 2 wt. %, nanotubes started to re-bundle in the epoxy matrix which negatively affected the final properties of epoxy composite.

Keywords: carbon fiber reinforced polymer, epoxy, multi-walled carbon nanotube, DMA, glass transition temperature

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Authors: Aghoutane Basma, Naama Amal, Talbi Hayat, El Manfalouti Hanae, Kartah Badreddine

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Aromatic and medicinal plants are used by man for different needs, including food and medicinal needs for their biological properties attributed mainly to phenolic compounds and for their antioxidant capacity. In our study, the aim is to compare three extraction solvents by evaluating the contents of phenolic compounds, the contents of flavonoids, and the antioxidant activities of extracts from different methods of extracting the aerial part of an endemic medicinal plant from Morocco. This activity was also confirmed by three methods (2,2-diphenyl-1-picrylhydrazyl (DPPH), antioxidant reducing power of iron (FRAP), and total antioxidant capacity (CAT)). The results showed that this plant is rich in polyphenols and flavonoids, as well as it has a very important antioxidant capacity in whatever the solvent or the extraction method. This suggests the importance of using extracts from this plant as a new natural source of food additives and potent antioxidants in the food industry.

Keywords: endemic plant of Morocco, phenolic compound, solvent, extraction technique, antioxidant activity

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Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

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In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

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Authors: Zohreh Didar Yaser, Zanganeh Asadabadi

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The aim of this work is to open up the structure of lemon peel (Citrus × latifolia) with mild pretreatments. The effects of autoclave, microwave and ultrasonic with or without acid addition were investigated on the amount of glucose, soluble and insoluble lignin, furfural, yeast viability and bioethanol. The finding showed that autoclave- acid impregnated sample, has the highest glucose release from lignocellulose materials (14.61 and 14.95 g/l for solvent exposed and untreated sample, respectively) whereas at control sample glucose content was at its minimal level. Pretreatments cause decrease on soluble and insoluble lignin and the highest decrease cause by autoclave following with microwave and ultrasonic pretreatments (p≤5%). Moderate increase on furfural was seen at pretreated samples than control ones. Also, the most yeast viability and bioethanol content was belong to autoclave samples especially acid- impregnated ones (40.33%). Comparison between solvent treated and untreated samples indicated that significant difference was between two tested groups (p≤1%) in terms of lignin, furfural, cell viability and ethanol content but glucose didn’t show significant difference. It imply that solvent extraction don’t influences on glucose release from lignocellulose material of lemon peel but cause enhancement of yeast viability and bioethanol production.

Keywords: Bioethanol, Lemon peel, Pretreatments, Solvent Extraction

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Authors: Aleksandrs Kovalcuks, Mara Duma

Abstract:

Egg yolk oil is a concentrated source of egg bioactive compounds, such as fat-soluble vitamins, phospholipids, cholesterol, carotenoids and others. To extract lipids and other fat-soluble nutrients from liquid egg yolk, a two-step extraction process involving polar (ethanol) and non-polar (hexane) solvents were used. This extraction technique was based on egg yolk bioactive compounds polarities, where non-polar compound was extracted into non-polar hexane, but polar in to polar alcohol/water phase. But many egg yolk bioactive compounds are not strongly polar or non-polar. Egg yolk phospholipids, cholesterol and pigments are amphipatic (have both polar and non-polar regions) and their behavior in ethanol/hexane solvent system is not clear. The aim of this study was to clarify the behavior of phospholipids, cholesterol and carotenoids during extraction of egg yolk oil with ethanol and hexane and determine the loss of these compounds in egg yolk oil. Egg yolks and egg yolk oil were analyzed for phospholipids (phosphatidylcholine (PC) and phosphatidylethanolamine (PE)), cholesterol and carotenoids (lutein, zeaxanthin, canthaxanthin and β-carotene) content using GC-FID and HPLC methods. PC and PE are polar lipids and were extracted into polar ethanol phase. Concentration of PC in ethanol was 97.89% and PE 99.81% from total egg yolk phospholipids. Due to cholesterol’s partial extraction into ethanol, cholesterol content in egg yolk oil was reduced in comparison to its total content presented in egg yolk lipids. The highest amount of lutein and zeaxanthin was concentrated in ethanol extract. The opposite situation was observed with canthaxanthin and β-carotene, which became the main pigments of egg yolk oil.

Keywords: cholesterol, egg yolk oil, lutein, phospholipids, solvent extraction

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